Highly autonomous vehicles are expected to free human drivers from continuous driving tasks. Therefore, for highly autonomous vehicles, the secondary tasks that human drivers tend to involve in are significantly different from conventional vehicles. Understanding driver preferences for secondary tasks in highly autonomous vehicles is beneficial to improve the acceptance of the vehicles. This study adopted an online questionnaire to investigate and understand human drivers’ preferences for secondary tasks in highly autonomous vehicles in China. Moreover, drivers’ understanding of different secondary tasks was collected and analyzed. Further, we compared and examined the differences in the secondary subtask preferences of drivers with different individual characteristics (e.g., driving experience, motion sickness, and attitudes towards autonomous driving). This study contributes to providing the basis for the studies on driving safety analysis for highly autonomous vehicles.


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    Titel :

    Understanding Driver Preferences for Secondary Tasks in Highly Autonomous Vehicles


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Long, Shengzhao (Herausgeber:in) / Dhillon, Balbir S. (Herausgeber:in) / Li, Qingkun (Autor:in) / Wang, Zhenyuan (Autor:in) / Wang, Wenjun (Autor:in) / Yuan, Quan (Autor:in)

    Kongress:

    International Conference on Man-Machine-Environment System Engineering ; 2022 ; Beijing, China October 21, 2022 - October 23, 2022



    Erscheinungsdatum :

    2022-08-21


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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